HPLC-UV and HPLC-CAD chromatographic data fusion for the authentication of the geographical origin of palm oil.

Autor: Obisesan KA; Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira i Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain., Jiménez-Carvelo AM; Department of Analytical Chemistry, University of Granada, c/Fuentenueva, s.n., E-18071 Granada, Spain., Cuadros-Rodriguez L; Department of Analytical Chemistry, University of Granada, c/Fuentenueva, s.n., E-18071 Granada, Spain., Ruisánchez I; Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira i Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain. Electronic address: itziar.ruisanchez@urv.cat., Callao MP; Chemometrics, Qualimetric and Nanosensors Group, Department of Analytical and Organic Chemistry, Rovira i Virgili University, Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
Jazyk: angličtina
Zdroj: Talanta [Talanta] 2017 Aug 01; Vol. 170, pp. 413-418. Date of Electronic Publication: 2017 Apr 13.
DOI: 10.1016/j.talanta.2017.04.035
Abstrakt: Data fusion combined with a multivariate classification approach (partial least squares-discriminant analysis, PLS-DA) was applied to authenticate the geographical origin of palm oil. Data fusion takes advantage of the synergistic effect of information collected from more than one data source. In this study, data from liquid chromatography coupled to two detectors -ultraviolet (UV) and charged aerosol (CAD)- was fused by high- and mid-level data fusion strategies. Mid-level data fusion combines a few variables from each technique and then applies the classification technique. Principal component analysis and interval partial least squares were applied to obtain the variables selected. High-level data fusion combines the PLS-DA classification results obtained individually from the chromatographic technique with each detector. Fuzzy aggregation connective operators were used to make the combinations. Prediction rates varied between 73% and 98% for the individual techniques and between 87% and 100% and 93% and 100% for the mid- and high-level data fusion strategies, respectively.
(Copyright © 2017 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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